Aktivität: Vortrag oder Präsentation › Eingeladener Vortrag › Science-to-science
Beschreibung
In this paper I explore the tension between the necessity of scientific input for complex political decisions that have a technical aspect (‘technical-political decisions’) and the inherent unreliability of expert judgement. While modern crises—such as climate change, pandemics, and socio-economic decline—require technical knowledge that citizens and politicians often lack, experts are frequently compromised by cognitive and motivational biases. Among the failings are:
•Cognitive Biases: Experts are prone to ‘confirmation bias’ and the ‘spiral of conviction’, where increased knowledge leads to greater dogmatism.•Motivational Biases: Personal, financial, and political interests often colour scientific recommendations, particularly in medicine and economics.•Numerical Illiteracy: Experts frequently struggle with statistical concepts, such as confusing relative and absolute risk reductions or committing the prevalence fallacy.
To address these failures, I take up Jürgen Habermas’s democratic models but reject both technocratic approaches that grant experts a political monopoly, and Habermas’ own democratic approach. Instead, I advocate a decisionist model characterised by competition. By consulting multiple competing experts, the political system can better identify the spectrum of scientific discourse while incentivising experts to reduce their individual biases.